Imagers, such as for example charge coupled devices (CCD), complementary metal oxide semiconductor (CMOS) and others, are widely used in imaging applications including digital still and video cameras. A CMOS imager circuit includes a focal plane array of pixels, each one of the pixels including a photosensor, for example, a photogate, a photoconductor, a phototransistor or a photodiode for accumulating photo-generated charge in the specified portion of the substrate. Each pixel has a charge storage region, formed on or in the substrate, which is connected to the gate of an output transistor that is part of a readout circuit. The charge storage region may be constructed as a floating diffusion region. In some imager circuits, each pixel may include at least one electronic device such as a transistor for transferring charge from the photosensor to the storage region and one device, also typically a transistor, for resetting the storage region to a predetermined charge level prior to charge transference.
In a CMOS imager, the active elements of a pixel perform the functions of: (1) photon to charge conversion; (2) accumulation of image charge; (3) resetting the storage region to a known state; (4) transfer of charge to the storage region; (5) selection of a pixel for readout; and (6) output and amplification of signals representing pixel reset level and pixel charge. Photo charge may be amplified when it moves from the initial charge accumulation region to the storage region. The charge at the storage region is typically converted to a pixel output voltage by a source follower output transistor.
Exemplary CMOS imaging circuits, processing steps thereof, and detailed descriptions of the functions of various CMOS elements of an imaging circuit are described, for example, in U.S. Pat. Nos. 6,140,630; 6,204,524; 6,310,366; 6,326,652; 6,333,205; 6,376,868; 6,852,591, all of which are assigned to Micron Technology, Inc. The disclosures of each of the foregoing are hereby incorporated by reference herein in their entirety.
CMOS imagers typically have an array of pixels containing photosensors, where each pixel produces a signal corresponding to the intensity of light impinging on that element when an image is focused on the pixel array. The signals may then be digitized and stored, for example, for display of a corresponding image on a monitor or for providing hardcopy images or otherwise used to provide information about a captured image. The magnitude of the signal produced by each pixel is proportional to the intensity of light impinging on the respective photosensor.
For photosensors to capture a color image, they must be able to separately detect color components of a captured image. For example when using a Bayer pattern, as shown for example in FIG. 1, photons having a wavelength corresponding to a red, green or blue color are detected by respective red, green, and blue pixels (i.e., each pixel is sensitive only to one color or spectral band). For this to occur, a color filter array (CFA) is typically placed in front of the pixel array so that each pixel receives the light of the color of its associated filter according to a specific pattern, e.g., the Bayer pattern 10 of FIG. 1. Other color filter array patterns are also known in the art and are applicable as well.
As shown in FIG. 1, the Bayer pattern 10 is an array of repeating red (R), green (G), and blue (B) filters. A red pixel is a pixel covered by a red filter; similarly, a blue pixel or a green pixel is a pixel covered by a blue or a green filter, respectively. The pixels of FIG. 1 may be identified by coordinates, pi,j, to identify the color and the location of the pixel within the pixel array, where p indicates the color (R for red, B for blue, G for green), i indicates the row location, and j indicates the column location. For example, one row 15 includes a green pixel G1,1 in column one and a red pixel R1,2 in column two. Likewise, a next row 20 includes a blue pixel B2,1 in column one and a green pixel G2,2 in column two.
In the Bayer pattern 10, red pixels 11, green pixels 13 and blue pixels 12 are arranged so that alternating red 11 and green 13 pixels are in one row 15 of a pixel array, and alternating blue 12 and green 13 pixels are in a next row 20. These alternating rows 15, 20 are repeated throughout the pixel array. Thus, when the imager is read out, the pixel sequence for one row (i.e., row 15) reads GRGRGR, etc., and the sequence for the next row (i.e., row 20) reads BGBGBG, etc. While FIG. 1 depicts an array having only ten rows and ten columns, pixel arrays typically have hundreds or thousands of rows and columns of pixels.
Pixels of a pixel array may experience interference, or crosstalk, when neighboring pixels interfere with each other. One form of such interference is optical crosstalk. Other forms of such interference include electrical crosstalk. Crosstalk may cause different problems in a captured image, one of which is a phenomenon known as green imbalance, which is when the pixels in one green channel of a pixel array provide a different output signal than the pixels in the other green channel of the pixel array under the same illumination level.
An example of optical crosstalk is described with reference to FIG. 2. FIG. 2 illustrates a portion of a color filter array 35 having the Bayer pattern 10 in front of a portion of pixels 40 of a pixel array. For pixels 40 located, for example, on the periphery of the pixel array, light rays 30 from a lens, e.g. a camera lens, may be coming in at oblique angles. In FIG. 2, for example, the illumination in the red spectrum which passes through red filter 36 at an oblique angle substantially affects the response of the green pixel 43. This is because the light rays 30 are coming in at such an angle that the light passing through red filter 36 actually hits the green pixel 43 instead of the red pixel for which it is intended. The same type of effect would also occur for green pixels that are located adjacent to blue pixels. The magnitude of the affect of optical crosstalk on a specific pixel is a function of several factors, including, for example, the distance between the pixel and its neighboring pixels and the distance between a photo sensor and an overlying microlens. Optical crosstalk may affect pixels throughout the pixel array and is not limited in its effect to pixels located at the periphery. However, the magnitude of the interference will depend on the angle of incidence of the light rays and therefore will vary throughout a pixel array depending on the location of the pixel within the pixel array.
Electrical crosstalk occurs when electrical charge generated in the photo sensor of one pixel travels to be collected at or otherwise influences the signal of an adjacent pixel. Such crosstalk causes interferences between signals converted via the photo detecting device.
The crosstalk interference of the red and blue pixels with the green neighboring pixels may cause the green-red pixels and the green-blue pixels to appear differently, even in response to the same level of light stimulus. This occurrence is known as green imbalance. Green-red pixels are the green pixels which appear in the same rows as red pixels, e.g., row 15 of FIG. 1. Green-blue pixels are the green pixels which appear in the same rows as blue pixels, e.g., row 20 of FIG. 1. The greed-red and green-blue pixels appear differently because the blue pixels will have a different affect on the green-blue pixels than the red pixels will have on the green-red pixels. In turn, this causes the pixels of the two green channels to have different crosstalk effects.
The presence of green imbalance can degrade image quality unless special steps are taken to counteract that effect during image processing. An image captured of an evenly illuminated white field, for example, may result in responses of the green-red pixels being different than the green-blue pixels. If this effect is not corrected during image processing, the variation in response may show up as a fine checkerboard pattern overlaid on a captured image or as other forms of image artifacts. Therefore, this imbalance between the green-blue and the green-red pixels should be desirably corrected during image processing. Ideally, the crosstalk components of the green-blue and green-red pixel signals are normalized after green imbalance compensation, at which point any effect of crosstalk will no longer be apparent in the displayed image.
Various computational methods are known to exist to compensate for green imbalance, including methods utilizing local neighborhood operations. Existing local green balancing methods improve image quality, but may also yield abundant undesirable image artifacts. Accordingly, a method that delivers high-quality results for green imbalance compensation without adding undesirable artifacts is desired.